The advent of new computer technologies and networks has greatly improved connections between computer users, especially in the world of sales and commerce. Sales professionals (e.g., people or companies that derive their income from selling goods or products to other individuals or companies) rely on finding new customers to grow and develop both their own careers and the companies they work for.
Currently, various methods exist for improving the accuracy of such searches, allowing for improved efficiency for members who search through the system. Some methods include tracking member activity to determine what content a particular member prefers and presenting similar content. For example, a member's activity on a social network can be tracked to determine frequent purchases of an item from a particular vendor and present similar items to a user or similar vendors. However, similarities between content items are many times insufficient to make more nuanced recommendations to members. For the sales use case, the insights derived from the types of content being created and shared on a social network can be used to infer the buying intent of members, enabling sales professionals to reach out to potential leads at the precise moment when these buying signals occur and when the content items relate to the good and services being offered.
Like reference numerals refer to corresponding parts throughout the drawings.